Motor Band Sign in Motor Neuron Disease: A Marker for Upper Motor Neuron Involvement
Bibliographic record
Abstract
ABSTRACT: Background and Objective: The prevalence and role of the motor band sign (MBS) remain unclear in motor neuron disease. We report the frequency of MBS in amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS), its correlation with clinical upper motor neuron (UMN) signs, and prognostic value in ALS. Methods: We conducted a retrospective study of ALS, PLS, and controls with retrievable MRI between 2010 and 2018. We compared the frequencies of MBS across the three groups, and studied correlation between susceptibility-weighted MRI measurements in primary motor cortices and contralateral UMN features. Clinical outcomes were compared between ALS with and without MBS. Results: Thirteen ALS, 5 PLS, and 10 controls were included (median age 60 years, IQR 54–66 years; 14/28 males). MBS was present in 9/13 (69.2%, 95% CI 38.9–89.6%) and 4/5 (80.0%, 95% CI 29.9–99.0%) of ALS and PLS, respectively, and none in controls. 2/13 (15.4%, 95% CI 2.7–46.3%) ALS and 3/5 (60.0%, 95% CI 17.0–92.7%) PLS had MBS in the absence of corticospinal T2/FLAIR hyperintensity sign. Susceptibility measurements in left motor cortices had a significantly positive correlation with contralateral UMN signs in ALS (τb = 0.628, p = 0.03). Similar but nonsignificant trends was observed for right motor cortices in ALS (τb = 0.516, p = 0.07). There were no significant differences in mRS at last follow-up, mortality, or time from symptom onset to last follow-up between ALS patients with and without MBS. Conclusions: We provide limited evidence that MBS and susceptibility quantification measurements in motor cortices may serve as surrogate markers of UMN involvement in motor neuron disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".